Non physical measure valued solution of hyperbolic pde can not be reached by any viscous solution ,is it correct or not?

How to get PDE values?

If any one is providing PDE values how can we assure that the values are authanicate?

If any one can help out to find the correct answer with reference if available?

Hello All

I am trying to solve PDE using Haar wavelets. I have built all the necessary matrices H,p, and q. I was able to get the solution for a 1-D PDE such as u '' = f (x)

Now, for a 2-D problem, I took the Kronecker product of all the matrices mentioned above, H,p, and q, and solved it in a higher-dimensional space. The size of the matrix became N^2*N^2. I got the correct solution.

However, is there any way to solve a 2-D problem using an N*N matrix size?

my method starts by assuming uxx=sum of c* H(x,y)

where H(x,y)=kron(H,H) where H is N*N matrix represent haar wavelets in 1-D. H(x,y) becomes N^2*N^2

I see some papers using uxx=sum of c* H(x)*H(y). I tried this method, but I was not able to get the correct solution. I think in this way they are using the same matrix size(H)=N*N

I need more details for this method, and if there is a code, I would appreciate it.

Is this solution correct or not, knowing that the transform that was taken is the ElZaki transform?

Dear friends,

Is it a correct way to use a linear system with uncertainties instead of the main nonlinear system?why?

As I remember, the proposed background correction just removes inelastic tail without any assumptions about surface structure of sample.

Ronald Fisher characterized statistics as a branch of applied mathematics, concerned with (1) the study of populations, (2) the study of variation, and (3) the study of sources of data reduction.

However, there are some mathematicians that strongly disagree with this characterization - insisting that statistics is not a branch of applied mathematics, but rather a separate field like physics.

Are they correct?

I am exploring the performance of a measure that can be computed using different values of its parameters, so I have about 20 variables. I want to find out which of these variables are able to differentiate two groups. So, I want to know about the performance of the variables, rather than finding differences between the groups. Therefore, I don't really think that I am given myself multiple chances to find a difference between the two groups and so I am inflating the chances of getting significant differences by chance. Actually, I am considering from the begining that the groups are different. So, do I really need some correction if I compare the 20 variables between the groups?